Onlim is a software platform for content creation and content distribution on social media, chatbots and artificial assistants. The company also offers automated, personalized 1:1 communication with clients and prospects for unlocking new digital sales and communication channels via smart chatbot solutions.
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Onlim's Products & Differentiators
Conversational AI & Knowledge Graph Platform
Multichannel Conversational AI Platform built upon Knowledge Graphs
Latest Onlim News
Jul 13, 2020
Communication with customers and suppliers, as well as with employees and interested parties is rapidly shifting towards chatbots and voice assistants, and Conversational AI is really gaining momentum. With Conversational AI gaining more and more momentum, the question now is “how can we create truly meaningful conversations between humans and machines”? Companies face the challenge of generating knowledge from information and making it machine-readable and easily accessible. This is where Knowledge Graphs and Conversational AI come into play. In this article, we explain the interaction of the two technologies for you in detail. Conversations and knowledge are closely linked: without knowledge, there are no meaningful conversations, without conversations less knowledge can be generated, and no insights can be gained. What does this mean specifically? As our CEO Alexander Wahler says, “Chatbots and voice assistants are only as good as the underlying knowledge to which they have access to.” At the same time, every interaction between machine and human generates new knowledge which needs to be structured and modeled. Before we look at how that works, we need to understand what differentiates data and information from knowledge. DATA are raw facts in the shape of text, pictures, or videos, which need to be interpreted by the user (e.g. text in documents, a directory of pictures and videos). INFORMATION is structured facts, which are already categorized (e.g. events have a date, a place, and a performer) and are, therefore, more accessible to the user. KNOWLEDGE on the other hand offers the opportunity to give concrete answers or solve problems since the context and meaning of the information are known conclusions can be made or algorithms applied. This makes knowledge much more valuable than information. Nowadays, most companies possess vast amounts of data and information, which should ideally be converted into knowledge at the push of a button. If knowledge about product data, financial data, availabilities, regulations etc. were shown in a Knowledge Graph and accessible via natural language, i.e. as in the communication between two people, this would save various instances in companies a lot of time and work and could open up new potential. So why isn’t all information converted to Knowledge Graphs? If this was so easy, all the Googles and Amazons and Microsofts in the world would have already done it for us. While these companies already built their knowledge on Knowledge Graphs (e.g. Microsoft’s latest Office 365 Version ), most data is not available publicly and very specific to a company. Hence, it is up to the companies and organizations to process their data, convert it into knowledge and make it available in private or public communication or marketing channels. So what does that look like specifically? A Knowledge Graph is a knowledge database that enables the preparation and structuring of information, which creates knowledge. The term was first introduced by Google in 2012 and is now synonymous with a special type of knowledge representation. In a Knowledge Graph, entities are connected to each other, given attributes and placed in a thematic context. The basic structure consists of so-called nodes and edges with which knowledge is described (see Figure 1), the former represent the entities, the latter in turn describe the type of relationship between the individual entities. Exemplary modeling of a knowledge graph by Onlim Knowledge Graphs also offer the possibility of dynamically and quickly adding new links and context between information. Thus, Knowledge Graphs provide the optimal basis for artificial intelligence and, among other things Conversational AI. Conversational AI is the query of knowledge in natural language, either through voice assistants or in the form of text via chatbots. Specifically, this means that information that has been prepared and structured in the Knowledge Graph and thus generates knowledge, is made available for retrieval in a further step via Conversational AI. In the implementation, it is important for companies to both build on existing data, but at the same time define goals that should be achieved with knowledge generation. First and foremost, companies need to be clear about what they want to achieve with their data and what the value of this data is. Do you digitize to archive? Or do you provide knowledge to support your decision making in many situations or even just to get one correct answer to a specific question for solving a problem? This is exactly what Onlim does by combining Knowledge Graphs and Conversational AI! According to IBM , data is valuable if it reduces the amount of time, effort, and resources needed to solve problems or make good decisions. To learn more about the symbiosis of Conversational AI and Knowledge Graphs , from the different levels of data preparation to practical approaches and use cases based on three exemplary industries (tourism, energy & retail), we invite you to download our whitepaper on “More knowledge for chatbots and voice assistants”. Remember the days when shopping used to be an outing, involving plans for the entire day, going from shop to shop until you actually liked something? Remember going to 5 different stores to compare the price of an electronic product before actually buying it from the cheapest store? Users today shop in the same way, except that they do not have to physically visit these stores anymore, and everything can be done sitting in one place at the click of a button. Online shopping has made it extremely convenient for users to never leave the luxury of their homes for the tedious task of shopping. How does the user make this purchase online? The internet today has so much data available, and a user’s past behavior, demographics, preferences have made it extremely easy for websites to target these users with products they will like. For example, if you log in to an online website such as Amazon, from where you usually buy your clothes, the websites know that you prefer loose-fitting jeans, darker shades, and a few particular brands based on your past purchases. The next time you log in, you will be shown clothes based on these preferences of yours, and it will become very easy for you to browse through these choices and make your selection. You do not have to spend the entire day browsing through all irrelevant clothing options. Consider the case of demographics. If as a young user, you normally prefer wearing jeans as in the example above, and you are shown options for ethnic clothing such as sarees, it will not be a pleasant experience for you. You would want to see options relevant to you. At the same time, suppose you are attending a wedding and require a saree this particular time, you would not want to see options for jeans and other western outfits. The biggest difference between these two scenarios is the customer’s intent. Both these times, the customer intended to buy two different things and would like to be shown different options. But according to the user’s past behavior, demographics, preferences, the website failed to satisfy the customer in the second scenario. According to Lisa Gevelber, marketers who solely rely on demographics to target customers risk missing out on about 70% of mobile shoppers, who could be potential customers. This is because they fail to gauge the shoppers’ in-the-moment purchase intentions. What if there was someone you could communicate with on the website and convey your intention? What if you could tell that person what exactly it was you were looking for and save time? A Segment survey has shown that 49% of buyers make impulse purchases after they receive a personalized shopping experience. In order to provide a personalized experience to the user, as a business owner, you need to be able to have a conversation with the users, understand their requirements, and assist them accordingly. A conversational AI does the perfect job of this and communicates with your users on your behalf. Conversational AI can be implemented across various channels such as Whatsapp, EMail, Messenger, and they can be text-based or voice-based. A Chatbot is adept at human conversation and assists users by identifying their intent and guides them to the right processes in the minimum possible number of steps, saving time and satisfying the user at the same time. According to invesp, chatbots help save 30% of customer support costs by boosting response time and answering about 80% of the routinely asked questions. According to Opus Research, by 2021, chatbots will see an investment of around 4.5 billion dollars. For people who prefer conversation through ‘talking’, there are Voice bots that are extremely intelligent. They stop speaking as soon as they hear the user talking, and start responding as soon as the user stops talking, much like an actual human. This provides a more personal touch to the customer who in turn is able to communicate his intent more clearly, enabling the bot to provide better customer experience. According to a Walker study, by 2020, the product and its price will be overtaken by customer experience as the brand differentiator. Enabling conversation with the customer through the use of bots is key to ensure a successful sale. This is where Engagely.ai comes in. Engagely is an enterprise-grade conversational AI platform. Enterprises use the Engagely platform to create conversational, omnichannel bots using its no-code technology. It supports 30 global languages and has top-notch security. While with behavioral data, demographic data, historical purchase, you can predict what a person wants to buy or what services he requires, but with the right customer intent, you can hit the bullseye. This goes a long way in customer retention and upselling. So is your business equipped with the capability to converse with your customers and gauge their intent? We hope this blog was useful for you. Please feel free to get in touch with us on firstname.lastname@example.org or visit our website — engagely.ai to know more. The ability of Conversational AI to effectively simulate human-like conversation has always fuelled a debate over whether AI-powered chatbots and virtual assistants can replace human agents entirely. There is a lot of excitement and discussion around the rapid development of AI technologies like Natural Language Processing (NLP), Deep Learning, and Machine Learning. But there is one component of Conversational AI that is usually less spoken of, without which these robust technologies will be ineffective. That is empathy. The Cambridge Dictionary has defined empathy as: the ability to share someone else’s feelings or experiences by imagining what it would be like to be in that person’s situation. Let us learn more about the importance of Empathy in improving Customer Experience with Intelligent Virtual Assistants. An Intelligent Virtual Assistant (IVA) is one of the strongest and most effective tools to create meaningful relationship with your customers at different touch points. What provides virtual assistants the power to transform customer experience is the amalgamation of different technologies and empathy. One competitive advantage that businesses should develop is how empathetic they are towards their customers and how much empathy they incorporate into their decision-making processes. As per the Empathy Index, 2016 by Harvard Business Review , the top 10 companies in the Global Empathy Index 2015 increased in value more than twice as much as the bottom 10, and generated 50% more earnings. In this context, the one question discussed frequently is: “Will IVAs be as empathetic as human agents?” There is no quantitative data as yet to prove that, but the development of Natural Language Processing and Deep Learning provides virtual assistants the necessary tools to understand emotions and predict the feelings of the consumers from the tone of their messages. How the IVAs respond to these messages is a direct result of how empathetic the conversation flow has been designed. Empathy becomes particularly crucial during a time of crisis. If there is one thing that has helped us survive the COVID-19 pandemic, it is empathy. Different bodies have used this superpower to solve problems faced by their people. Now, more than ever in human history, companies need to find better and more effective ways to communicate with their customers and enhance the level of customer service. There is a greater need for companies to understand the turbulence of emotions and feelings their customers are going through and communicate accordingly with them. A good Conversation Designer ensures that the Intelligent Virtual Assistants (IVA) are always equipped with empathic responses to build a better relationship with the customer. As Michelle Parayill, Senior Conversation Designer at Haptik rightly says, “Empathy is one of the keystones of Conversation Design. It’s important to avoid dry and robotic sounding copy when you’re trying to communicate in an empathetic and humane manner. A simple variation, like saying “I’m listening and completely understand how you feel” as opposed to “ok”, can go a long way.” Let us now take a look at a few things you need to keep in mind while developing empathetic IVAs: 1. Start from the start The purpose of developing virtual assistants with empathy is to make them more human-like. Every human being on this planet has a name, a face and a personality. While inculcating these factors in IVAs, be mindful about the overall positioning strategy of your brand in the minds of the customers. The goal here is to make the machine sound less robotic and more human. 2. Do not push but assist No one likes to be sold to. They purchase your product or services to solve their problems, and not to drive your business. Do not make product recommendations with every message but assist them in understanding their problems and how your product or service can help them in solving the problem. If the customer is adamant about sharing personal or confidential information or does not want to purchase your product right away, make sure you communicate that you understand and support their decision. 3. Help them to exit The primary purpose of an IVA is not to have conversations, but to enhance the customer experience. If at any point, the customer wishes to talk to a human agent, make sure there is a process in place for that. Help your customers with getting in touch with the human agent, ask for their feedback on the interaction with the human agent, and make sure their queries are resolved. 4. Unleash the power of Emotion AI Emotion AI helps businesses to understand consumer behavior with respect to how they react to different situations. Chatbots can explore Emotion AI to recognize the urgency and applicability of consumers by the tone and words of their message. Implementing an empathetic Intelligent Virtual Assistant (IVA) solution can significantly boost customer satisfaction for brands across verticals. Here are a few reasons why your brand should definitely look to add empathy to your virtual assistants: 1. Better relationship with customers Customers love to interact with chatbots and virtual assistants that do not act like robots and machines. Once the customers are comfortable with sharing information, the brands can develop better relationships with them, since they exactly know the customers’ feelings and thoughts. 2. Helps in building a brand Empathy can make your customers feel understood. A conversation powered with empathy will increase customers’ likability towards your brand. Once the customer has become a loyal customer, he will become the brand advocate for your company and help you in the brand building process. The best part? It is free! 3. Helps enhance customer experience Conversations driven by empathetic virtual assistants will inspire customers to talk to the IVA for a longer period. This will help the company to gather more data pertinent to their business. The company will now leverage this data to create better experiences for customers interacting with the IVA in the future. From the above-mentioned points, we have understood how important a role empathy plays in driving business growth. Empathy has played a huge role in transforming how customers perceive Conversational AI, which in turn has had a positive impact on its adoption by businesses. Daniel Kahneman, 2002 Nobel Prize winner said in his 2011 book “Thinking, Fast and Slow” that “We are not thinking machines that feel, we are feeling machines that think.” And as far as possible, the same should be true for our Intelligent Virtual Assistants! Want to develop an Intelligent Virtual Assistant for your brand? Get in Touch Quick read ➨ Animate 3D transforms 2D videos into 3D animations, for use in AR and VR, games and other applications ➨ DeepMotion used the example of a 30-second dancing animation, which can take approximately two weeks for an animator to keyframe manually. Using Animate 3D, an animator needs only convert video clips to the target animation and do some clean-up, which takes a matter of days ➨ Animate 3D is in alpha right now and DeepMotion is planning to release animation retargeting tutorials for Unity, Unreal Engine 4, Maya and Blender in the coming weeks to assist with the development process The story DeepMotion, the developer of smarter movement technology for virtual applications, has launched a new cloud-based service that eliminates the need for expensive suits and hardware typically required for full-body capture. Animate 3D transforms 2D videos into 3D animations, for use in AR and VR, games and other applications. A DeepMotion spokesperson told VRWorldTech that Animate 3D will prove a boon to game development studios and content creation teams, in terms of resources and time saved. The spokesperson said: “Animate 3D can generate a 3D animation from a 2D video source in a matter of minutes using our Perceptive Motion Brain technology. The current methods for creating traditional animations are motion capture and keyframe animation, which both involve drastically higher development time and costs.” “Traditional motion capture hardware is very expensive costing around $30,000 to $300,000 and is not affordable by all game development studios or content creation teams. It will also take a very involved process to rent the space, plan the staff, perform the capture, and perform the data clean-up, taking weeks if not months time to complete a capture project.” DeepMotion used the example of a 30-second dancing animation, which can take approximately two weeks for an animator to keyframe manually. Using Animate 3D, an animator needs only convert video clips to the target animation and do some clean-up, which takes a matter of days. DeepMotion believes that Animate 3D can provide a solid platform for new creators of all kinds of content. “If you take a technology that was only previously available to companies or individuals with capital and suddenly it’s available to a casual creator, it opens a lot of doors for new ideas and new content to flourish,” the DeepMotion spokesperson explained. “For animators specifically, if you are able to generate an animation that is 80% finished, that is going to save you a ton of time compared to needing to create the same animation from scratch.” [embedded content] Animate 3D is in alpha right now and DeepMotion is planning to release animation retargeting tutorials for Unity, Unreal Engine 4, Maya and Blender in the coming weeks to assist with the development process. DeepMotion is interested in receiving feedback during the alpha release. The spokesperson told VRWorldTech: “The entire platform is new, from the sign-up process to the animation viewer in the browser.” “Our goal is to make a product and process that creators find intuitive and assists them in the development of their projects. In addition to that, we are always looking to improve the AI on the backend for better animation results, so any feedback on what users are looking for to create an animation they’re excited to use is definitely helpful as well.” DeepMotion, founded in 2014, aims to use the real world as its muse for virtual motion. Using the Perceptive Motion Brain platform, DeepMotion is able to capture and create accurate, natural 3D character motion from 2D video and imagery. Its Generative Motion Brain is able to step in and lend the considerable weight of the company’s AI technology to do the “heavy lifting” of simulation, DeepMotion founder and chief executive officer Kevin He told VRWorldTech Magazine earlier this year. Any tool that can save animators’ time and resources demands serious consideration, and the Animate 3D alpha is an excellent opportunity to test both ease of use and the quality of results. Let VRWorldTech know how you get on with Animate 3D via Twitter , LinkedIn , Facebook or email@example.com . Main image: Animators and creators interested in trying Animate 3D can sign up for access now
Onlim Frequently Asked Questions (FAQ)
When was Onlim founded?
Onlim was founded in 2015.
Where is Onlim's headquarters?
Onlim's headquarters is located at 6410 Telfs, Wien.
What is Onlim's latest funding round?
Onlim's latest funding round is Corporate Minority - II.
Who are the investors of Onlim?
Investors of Onlim include feratel media technologies and weXelerate.
What products does Onlim offer?
Onlim's products include Conversational AI & Knowledge Graph Platform.
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